‘AIM4SafeBaby®’ (Artificial Intelligence monitoring for Safe baby birth)
–AIM4SafeBaby® –(人工智能监控婴儿安全分娩)
基本信息
- 批准号:10065844
- 负责人:
- 金额:$ 58.08万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Collaborative R&D
- 财政年份:2024
- 资助国家:英国
- 起止时间:2024 至 无数据
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
The MBRRACE-UK report highlights 2292 stillbirths in 2020 and RCOG (Royal College of Obstetricians and Gynecologists)'s Each Baby Counts report; 2022 reiterates that, in 2018 alone, amongst 1145 babies, 11 % of babies died during labour, 75% of babies suffered from severe brain injury and whilst 14% died in 1st month of their life. The world's live birth rate is 701,277,931 per year \[1\] and 3% of these births (21,038,337 births/year) will have complicated and delayed caesarean sections. CDC (Centers for Disease Control and Prevention.) reports, in the USA, 50,000 mothers are severely injured & 700 die annually. 60% of these deaths and half the injuries could be avoided with proper care\[Vital Signs The report (CDC), May 2019\].There is clearly a need for better monitoring of the labour data. The Healthcare Safety Investigation Branch (HSIB) recommends that the Department of Health and Social Care commission a review to improve the reliability of existing assessment tools for fetal growth and fetal heart rate to minimise the risk for babies \[Safety recommendation R/2021/148\].The AIM4SafeBaby project addresses this need and will create an innovative clinical decision support system that converts labour data into knowledge-based guidelines for safer baby delivery. This innovative monitoring device will monitor the birth process and help clinicians, labouring women, and their birth partners choose the safest birth option and the benefits versus risks of all the available options. This will help timely and accurate management of the birth and will reduce the birth trauma to the mother and the baby.'AIM4SafeBaby' solution offers a game-changing solution to clinicians. Currently, there is no technology or integrated solution able to offer a complete picture of the labour process and highlight the risks for taking educated decisions towards a safe and smooth birth process for both mother and baby. Existing labour monitoring devices like EFM(Electronic Foetal Monitoring) and CTG(cardiotocography) offer findings that cannot be relied upon as the sole source to make decisions in real-time during ongoing labour. Even highly trained health professionals sometimes struggle to interpret electronic monitor readings accurately and reliably. An off-site senior obstetrician may be called upon to help, often losing critical time for the baby's health. Hence there is an enormous scope to minimise human errors with our AI-based CTG monitoring and prediction tool.\[1\]Ref: United Nations, Department of Economic and Social Affairs, Population Division, 2019
MBRRACE-UK报告强调了2020年的2292例死产和RCOG(皇家妇产科医师学院)的《每个婴儿都很重要》报告; 2022年重申,仅在2018年,在1145名婴儿中,11%的婴儿在分娩过程中死亡,75%的婴儿患有严重的脑损伤,14%的婴儿在出生后的第一个月内死亡。全世界每年的活产率为701,277,931 [1],其中3%(21,038,337出生/年)将进行复杂和延迟的剖腹产。CDC(美国疾病控制与预防中心)据报道,在美国,每年有5万名母亲严重受伤,700人死亡。这些死亡中的60%和一半的伤害可以通过适当的护理避免[Vital Signs The report(CDC),May 2019]。显然需要更好地监测劳动力数据。医疗保健安全调查分支(HSIB)建议卫生和社会护理部进行审查,以提高现有胎儿生长和胎儿心率评估工具的可靠性,以最大限度地降低婴儿风险[安全建议R/2021/148]。AIM 4SafeBaby项目满足了这一需求,并将创建一个创新的临床决策支持系统,将分娩数据转化为知识-基于更安全的婴儿分娩指南。这种创新的监测设备将监测分娩过程,并帮助临床医生、分娩妇女及其分娩伴侣选择最安全的分娩方案,以及所有可用方案的益处与风险。这将有助于及时准确地管理分娩,并减少对母亲和婴儿的出生创伤。“AIM 4SafeBaby”解决方案为临床医生提供了一个改变游戏规则的解决方案。目前,没有技术或综合解决方案能够提供分娩过程的全貌,并强调为母亲和婴儿安全顺利的分娩过程做出明智决定的风险。现有的分娩监测设备,如EFM(电子胎儿监测)和CTG(心脏分娩图),提供的结果不能作为唯一的来源,在正在进行的分娩过程中实时做出决定。即使是训练有素的卫生专业人员有时也很难准确可靠地解读电子监测仪读数。一个非现场的高级产科医生可能会被要求提供帮助,往往失去了婴儿健康的关键时间。因此,我们基于人工智能的CTG监测和预测工具可以极大地减少人为错误。[1]参考:联合国经济和社会事务部人口司,2019年
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
其他文献
吉治仁志 他: "トランスジェニックマウスによるTIMP-1の線維化促進機序"最新医学. 55. 1781-1787 (2000)
Hitoshi Yoshiji 等:“转基因小鼠中 TIMP-1 的促纤维化机制”现代医学 55. 1781-1787 (2000)。
- DOI:
- 发表时间:
- 期刊:
- 影响因子:0
- 作者:
- 通讯作者:
LiDAR Implementations for Autonomous Vehicle Applications
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
- 通讯作者:
吉治仁志 他: "イラスト医学&サイエンスシリーズ血管の分子医学"羊土社(渋谷正史編). 125 (2000)
Hitoshi Yoshiji 等人:“血管医学与科学系列分子医学图解”Yodosha(涉谷正志编辑)125(2000)。
- DOI:
- 发表时间:
- 期刊:
- 影响因子:0
- 作者:
- 通讯作者:
Effect of manidipine hydrochloride,a calcium antagonist,on isoproterenol-induced left ventricular hypertrophy: "Yoshiyama,M.,Takeuchi,K.,Kim,S.,Hanatani,A.,Omura,T.,Toda,I.,Akioka,K.,Teragaki,M.,Iwao,H.and Yoshikawa,J." Jpn Circ J. 62(1). 47-52 (1998)
钙拮抗剂盐酸马尼地平对异丙肾上腺素引起的左心室肥厚的影响:“Yoshiyama,M.,Takeuchi,K.,Kim,S.,Hanatani,A.,Omura,T.,Toda,I.,Akioka,
- DOI:
- 发表时间:
- 期刊:
- 影响因子:0
- 作者:
- 通讯作者:
的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('', 18)}}的其他基金
An implantable biosensor microsystem for real-time measurement of circulating biomarkers
用于实时测量循环生物标志物的植入式生物传感器微系统
- 批准号:
2901954 - 财政年份:2028
- 资助金额:
$ 58.08万 - 项目类别:
Studentship
Exploiting the polysaccharide breakdown capacity of the human gut microbiome to develop environmentally sustainable dishwashing solutions
利用人类肠道微生物群的多糖分解能力来开发环境可持续的洗碗解决方案
- 批准号:
2896097 - 财政年份:2027
- 资助金额:
$ 58.08万 - 项目类别:
Studentship
A Robot that Swims Through Granular Materials
可以在颗粒材料中游动的机器人
- 批准号:
2780268 - 财政年份:2027
- 资助金额:
$ 58.08万 - 项目类别:
Studentship
Likelihood and impact of severe space weather events on the resilience of nuclear power and safeguards monitoring.
严重空间天气事件对核电和保障监督的恢复力的可能性和影响。
- 批准号:
2908918 - 财政年份:2027
- 资助金额:
$ 58.08万 - 项目类别:
Studentship
Proton, alpha and gamma irradiation assisted stress corrosion cracking: understanding the fuel-stainless steel interface
质子、α 和 γ 辐照辅助应力腐蚀开裂:了解燃料-不锈钢界面
- 批准号:
2908693 - 财政年份:2027
- 资助金额:
$ 58.08万 - 项目类别:
Studentship
Field Assisted Sintering of Nuclear Fuel Simulants
核燃料模拟物的现场辅助烧结
- 批准号:
2908917 - 财政年份:2027
- 资助金额:
$ 58.08万 - 项目类别:
Studentship
Assessment of new fatigue capable titanium alloys for aerospace applications
评估用于航空航天应用的新型抗疲劳钛合金
- 批准号:
2879438 - 财政年份:2027
- 资助金额:
$ 58.08万 - 项目类别:
Studentship
Developing a 3D printed skin model using a Dextran - Collagen hydrogel to analyse the cellular and epigenetic effects of interleukin-17 inhibitors in
使用右旋糖酐-胶原蛋白水凝胶开发 3D 打印皮肤模型,以分析白细胞介素 17 抑制剂的细胞和表观遗传效应
- 批准号:
2890513 - 财政年份:2027
- 资助金额:
$ 58.08万 - 项目类别:
Studentship
CDT year 1 so TBC in Oct 2024
CDT 第 1 年,预计 2024 年 10 月
- 批准号:
2879865 - 财政年份:2027
- 资助金额:
$ 58.08万 - 项目类别:
Studentship
Understanding the interplay between the gut microbiome, behavior and urbanisation in wild birds
了解野生鸟类肠道微生物组、行为和城市化之间的相互作用
- 批准号:
2876993 - 财政年份:2027
- 资助金额:
$ 58.08万 - 项目类别:
Studentship
相似海外基金
I-Corps: Translation Potential of a Secure Data Platform Empowering Artificial Intelligence Assisted Digital Pathology
I-Corps:安全数据平台的翻译潜力,赋能人工智能辅助数字病理学
- 批准号:
2409130 - 财政年份:2024
- 资助金额:
$ 58.08万 - 项目类别:
Standard Grant
Planning: Artificial Intelligence Assisted High-Performance Parallel Computing for Power System Optimization
规划:人工智能辅助高性能并行计算电力系统优化
- 批准号:
2414141 - 财政年份:2024
- 资助金额:
$ 58.08万 - 项目类别:
Standard Grant
REU Site: CyberAI: Cybersecurity Solutions Leveraging Artificial Intelligence for Smart Systems
REU 网站:CyberAI:利用人工智能实现智能系统的网络安全解决方案
- 批准号:
2349104 - 财政年份:2024
- 资助金额:
$ 58.08万 - 项目类别:
Standard Grant
EAGER: Artificial Intelligence to Understand Engineering Cultural Norms
EAGER:人工智能理解工程文化规范
- 批准号:
2342384 - 财政年份:2024
- 资助金额:
$ 58.08万 - 项目类别:
Standard Grant
Reversible Computing and Reservoir Computing with Magnetic Skyrmions for Energy-Efficient Boolean Logic and Artificial Intelligence Hardware
用于节能布尔逻辑和人工智能硬件的磁斯格明子可逆计算和储层计算
- 批准号:
2343607 - 财政年份:2024
- 资助金额:
$ 58.08万 - 项目类别:
Standard Grant
Artificial intelligence in education: Democratising policy
教育中的人工智能:政策民主化
- 批准号:
DP240100602 - 财政年份:2024
- 资助金额:
$ 58.08万 - 项目类别:
Discovery Projects
Reassessing the Appropriateness of currently-available Data-set Protection Levers in the era of Artificial Intelligence
重新评估人工智能时代现有数据集保护手段的适用性
- 批准号:
23K22068 - 财政年份:2024
- 资助金额:
$ 58.08万 - 项目类别:
Grant-in-Aid for Scientific Research (B)
TRUST2 - Improving TRUST in artificial intelligence and machine learning for critical building management
TRUST2 - 提高关键建筑管理的人工智能和机器学习的信任度
- 批准号:
10093095 - 财政年份:2024
- 资助金额:
$ 58.08万 - 项目类别:
Collaborative R&D
QUANTUM-TOX - Revolutionizing Computational Toxicology with Electronic Structure Descriptors and Artificial Intelligence
QUANTUM-TOX - 利用电子结构描述符和人工智能彻底改变计算毒理学
- 批准号:
10106704 - 财政年份:2024
- 资助金额:
$ 58.08万 - 项目类别:
EU-Funded
Application of artificial intelligence to predict biologic systemic therapy clinical response, effectiveness and adverse events in psoriasis
应用人工智能预测生物系统治疗银屑病的临床反应、有效性和不良事件
- 批准号:
MR/Y009657/1 - 财政年份:2024
- 资助金额:
$ 58.08万 - 项目类别:
Fellowship